"bar"
    ],
    "images": [
        {
            "url": "http://example.com/baz.jpg",
            "name": "The Foo live"
        },
        {
            "url": "http://example.com/dave.jpg",
            "name": "The Baz"
        }
    ]
}
```

!!! info "informação"
    Note como o campo `images` agora tem uma lista de objetos de image.

## Modelos profundamente aninhados

from fastapi import FastAPI
from pydantic import BaseModel, HttpUrl

app = FastAPI()


class Image(BaseModel):
    url: HttpUrl
    name: str


class Item(BaseModel):
    name: str
    description: str | None = None
    price: float
    tax: float | None = None
    tags: set[str] = set()
    images: list[Image] | None = None


class Offer(BaseModel):
    name: str
    description: str | None = None

from fastapi import FastAPI
from pydantic import BaseModel, HttpUrl

app = FastAPI()


class Image(BaseModel):
    url: HttpUrl
    name: str


class Item(BaseModel):
    name: str
    description: Union[str, None] = None
    price: float
    tax: Union[float, None] = None
    tags: Set[str] = set()
    images: Union[List[Image], None] = None


@app.put("/items/{item_id}")

## Bodys aus reinen Listen

Wenn Sie möchten, dass das äußerste Element des JSON-Bodys ein JSON-`array` (eine Python-`list`e) ist, können Sie den Typ im Funktionsparameter deklarieren, mit der gleichen Syntax wie in Pydantic-Modellen:

```Python
images: List[Image]
```

oder in Python 3.9 und darüber:

```Python
images: list[Image]
```

so wie in:

    ```

!!! info
    👀 ❔ `Offer` ✔️ 📇 `Item`Ⓜ, ❔ 🔄 ✔️ 📦 📇 `Image`Ⓜ

## 💪 😁 📇

🚥 🔝 🎚 💲 🎻 💪 👆 ⌛ 🎻 `array` (🐍 `list`), 👆 💪 📣 🆎 🔢 🔢, 🎏 Pydantic 🏷:

```Python
images: List[Image]
```

⚖️ 🐍 3️⃣.9️⃣ & 🔛:

```Python
images: list[Image]
```

:

=== "🐍 3️⃣.6️⃣ & 🔛"

    ```Python hl_lines="15"

        "rock",
        "metal",
        "bar"
    ],
    "images": [
        {
            "url": "http://example.com/baz.jpg",
            "name": "The Foo live"
        },
        {
            "url": "http://example.com/dave.jpg",
            "name": "The Baz"
        }
    ]
}
```

!!! info
    请注意 `images` 键现在具有一组 image 对象是如何发生的。

## 深度嵌套模型

你可以定义任意深度的嵌套模型：

## Bodies of pure lists

If the top level value of the JSON body you expect is a JSON `array` (a Python `list`), you can declare the type in the parameter of the function, the same as in Pydantic models:

```Python
images: List[Image]
```

or in Python 3.9 and above:

```Python
images: list[Image]
```

as in:

=== "Python 3.9+"

{!../../../docs_src/body_nested_models/tutorial007.py!}
```

!!! info "情報"
    `Offer`は`Item`のリストであり、オプションの`Image`のリストを持っていることに注目してください。

## 純粋なリストのボディ

期待するJSONボディのトップレベルの値がJSON`array`（Pythonの`list`）であれば、Pydanticモデルと同じように、関数のパラメータで型を宣言することができます:

```Python
images: List[Image]
```

以下のように:

```Python hl_lines="15"
{!../../../docs_src/body_nested_models/tutorial008.py!}
```

from fastapi import FastAPI
from pydantic import BaseModel, HttpUrl

app = FastAPI()


class Image(BaseModel):
    url: HttpUrl
    name: str


class Item(BaseModel):
    name: str
    description: Union[str, None] = None
    price: float
    tax: Union[float, None] = None
    tags: Set[str] = set()
    images: Union[List[Image], None] = None


class Offer(BaseModel):
    name: str

{!../../../docs_src/body_nested_models/tutorial007.py!}
```

!!! info "정보"
    `Offer`가 선택사항 `Image` 리스트를 차례로 갖는 `Item` 리스트를 어떻게 가지고 있는지 주목하세요

## 순수 리스트의 본문

예상되는 JSON 본문의 최상위 값이 JSON `array`(파이썬 `list`)면, Pydantic 모델에서와 마찬가지로 함수의 매개변수에서 타입을 선언할 수 있습니다:

```Python
images: List[Image]
```

이를 아래처럼:

```Python hl_lines="15"
{!../../../docs_src/body_nested_models/tutorial008.py!}
```